J Biomed Inform - Development and validation of a continuous measure of patient condition using the Electronic Medical Record.


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Patient condition is a key element in communication between clinicians. However, there is no generally accepted definition of patient condition that is independent of diagnosis and that spans acuity levels. We report the development and validation of a continuous measure of general patient condition that is independent of diagnosis, and that can be used for medical-surgical as well as critical care patients. A survey of Electronic Medical Record data identified common, frequently collected non-static candidate variables as the basis for a general, continuously updated patient condition score. We used a new methodology to estimate in-hospital risk associated with each of these variables. A risk function for each candidate input was computed by comparing the final pre-discharge measurements with 1-year post-discharge mortality. Step-wise logistic regression of the variables against 1-year mortality was used to determine the importance of each variable. The final set of selected variables consisted of 26 clinical measurements from four categories: nursing assessments, vital signs, laboratory results and cardiac rhythms. We then constructed a heuristic model quantifying patient condition (overall risk) by summing the single-variable risks. The model's validity was assessed against outcomes from 170,000 medical-surgical and critical care patients, using data from three US hospitals. Outcome validation across hospitals yields an area under the receiver operating characteristic curve(AUC) of =0.92 when separating hospice/deceased from all other discharge categories, an AUC of =0.93 when predicting 24-h mortality and an AUC of 0.62 when predicting 30-day readmissions. Correspondence with outcomes reflective of patient condition across the acuity spectrum indicates utility in both medical-surgical units and critical care units. The model output, which we call the Rothman Index, may provide clinicians with a longitudinal view of patient condition to help address known challenges in caregiver communication, continuity of care, and earlier detection of acuity trends.

Resumo Limpo

patient condit key element communic clinician howev general accept definit patient condit independ diagnosi span acuiti level report develop valid continu measur general patient condit independ diagnosi can use medicalsurg well critic care patient survey electron medic record data identifi common frequent collect nonstat candid variabl basi general continu updat patient condit score use new methodolog estim inhospit risk associ variabl risk function candid input comput compar final predischarg measur year postdischarg mortal stepwis logist regress variabl year mortal use determin import variabl final set select variabl consist clinic measur four categori nurs assess vital sign laboratori result cardiac rhythm construct heurist model quantifi patient condit overal risk sum singlevari risk model valid assess outcom medicalsurg critic care patient use data three us hospit outcom valid across hospit yield area receiv oper characterist curveauc separ hospicedeceas discharg categori auc predict h mortal auc predict day readmiss correspond outcom reflect patient condit across acuiti spectrum indic util medicalsurg unit critic care unit model output call rothman index may provid clinician longitudin view patient condit help address known challeng caregiv communic continu care earlier detect acuiti trend

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